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Security Feeds

by io.github.pipeworx-io

Polymarket Arbitrage

polymarket_arbitrage
Read-onlyIdempotent

Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a trending_scan of the top ~200 markets by weekly volume; pass event for the strongest per-event partition_check, or topic for a themed cross-event scan. event (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). topic (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventNoSingle-event mode (use this if you know the specific Polymarket event): event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k". Full Polymarket URLs also accepted.
topicNoCross-event mode (use this if you want to scan related events across the platform): a topic or seed question like "Fed rate decision" or "Strait of Hormuz traffic returns to normal". Tool searches Polymarket for related events and checks monotonicity across them.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds extensive behavioral context: cross-event similarity (Jaccard >=0.30), partition filter (placeholder slugs, >20% returns null), fill check (theoretical vs realizable edge, thin_legs). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

First sentence front-loads purpose. Some redundancy in explaining partition_check twice, but overall efficient for the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers default behavior, both modes, fill check, return fields, and references sibling tool for custom sizing. No gaps for a complex analytical tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Provides rich meaning beyond schema: recommended usage, accepted formats (full URLs), behavioral differences (partition_check for event, cross-event scanning for topic).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it finds arbitrage opportunities via monotonicity violations and partition-sum checks. Distinguishes between trending_scan, event mode, and topic mode with specific use cases.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use each mode: no args for trending, event for specific market, topic for cross-event. Also includes when not to trade (fill check with non-positive edge).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation2/5

The ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded trio creates real selection ambiguity — beta is currently identical to the stable router, and grounded shares the same routing with an added evidence step. Polymarket tools also overlap (polymarket_edges vs polymarket_arbitrage both surface structural arbitrage), and entity_profile/recent_changes both pull filings and news.

Naming Consistency4/5

Most tools follow a snake_case verb_noun pattern (resolve_entity, list_feeds, validate_claim, compare_entities). Minor deviations exist — bare verbs (remember, recall, forget, subscribe, unsubscribe) and noun-first names (entity_profile, recent_changes, pipeworx_trending) — but the overall convention is consistent and readable.

Tool Count2/5

34 tools is excessive for a server nominally named 'Security Feeds' — only three tools actually relate to security feeds. Even as a broad data-research platform, the surface feels bloated with five near-exclusive Polymarket tools, three memory tools, and four subscription-lifecycle tools that could be consolidated.

Completeness4/5

For the actual domain revealed by the tools (data research, entity intelligence, prediction markets, subscriptions, feeds), coverage is strong: resolution, profiles, changes, comparison, claim verification, memory CRUD, subscription lifecycle, and feed operations are all present. Minor gaps include no subscription-update tool and no direct feed-search tool, but the ask_pipeworx router compensates.

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